Transformed symmetric models

For the first time, we introduce a class of transformed symmetric models to extend the Box and Cox models to more general symmetric models. The new class of models includes all symmetric continuous distributions with a possible non-linear structure for the mean and enables the fitting of a wide range of models to several data types. The proposed methods offer more flexible alternatives to Box-Cox or other existing procedures. We derive a very simple iterative process for fitting these models by maximum likelihood, whereas a direct unconditional maximization would be more difficult. We give simple formulae to estimate the parameter that indexes the transformation of the response variable and the moments of the original dependent variable which generalize previous published results. We discuss inference on the model parameters. The usefulness of the new class of models is illustrated in one application to a real dataset.

Naming the Bonaire banded box jelly, Tamoya ohboya, n. sp. (Cnidaria: Cubozoa: Carybdeida: Tamoyidae)

A new species of cubozoan jellyfish has been discovered in shallow waters of Bonaire, Netherlands ( Dutch Caribbean). Thus far, approximately 50 sightings of the species, known commonly as the Bonaire banded box jelly, are recorded, and three specimens have been collected. Three physical encounters between humans and the species have been reported. Available evidence suggests that a serious sting is inflicted by this medusa. To increase awareness of the scientific disciplines of systematics and taxonomy, the public has been involved in naming this new species. The Bonaire banded box jelly, Tamoya ohboya, n. sp., can be distinguished from its close relatives T. haplonema from Brazil and T. sp. from the southeastern United States by differences in tentacle coloration, cnidome, and mitochondrial gene sequences. Tamoya ohboya n. sp. possesses striking dark brown to reddish-orange banded tentacles, nematocyst warts that densely cover the animal, and a deep stomach. We provide a detailed comparison of nematocyst data from Tamoya ohboya n. sp., T. haplonema from Brazil, and T. sp. from the Gulf of Mexico.

Low-level Laser Therapy Improves Skeletal Muscle Performance, Decreases Skeletal Muscle Damage and Modulates mRNA Expression of COX-1 and COX-2 in a Dose-dependent Manner

We tested if modulation in mRNA expression of cyclooxygenase isoforms (COX-1 and COX-2) can be related to protective effects of phototherapy in skeletal muscle. Thirty male Wistar rats were divided into five groups receiving either one of four laser doses (0.1, 0.3, 1.0 and 3.0 J) or a no-treatment control group. Laser irradiation (904 nm, 15 mW average power) was performed immediately before the first contraction for treated groups. Electrical stimulation was used to induce six tetanic tibial anterior muscle contractions. Immediately after sixth contraction, blood samples were collected to evaluate creatine kinase activity and muscles were dissected and frozen in liquid nitrogen to evaluate mRNA expression of COX-1 and COX-2. The 1.0 and 3.0 J groups showed significant enhancement (P < 0.01) in total work performed in six tetanic contractions compared with control group. All laser groups, except the 3.0 J group, presented significantly lower post-exercise CK activity than control group. Additionally, 1.0 J group showed increased COX-1 and decreased COX-2 mRNA expression compared with control group and 0.1, 0.3 and 3.0 J laser groups (P < 0.01). We conclude that pre-exercise infrared laser irradiation with dose of 1.0 J enhances skeletal muscle performance and decreases post-exercise skeletal muscle damage and inflammation.

Celecoxib prevents tumor growth in an animal model by a COX-2 independent mechanism

Nonsteroidal antiinflammatory drugs (NSAIDs) have been shown to reduce cell growth in several tumors. Among these possible antineoplastic drugs are cyclooxygenase-2 (COX-2)-selective drugs, such as celecoxib, in which antitumoral mechanisms were evaluated in rats bearing Walker-256 (W256) tumor. W256 carcinosarcoma cells were inoculated subcutaneously (10(7) cells/rat) in rats submitted to treatment with celecoxib (25 mg kg(-1)) or vehicle for 14 days. Tumor growth, body-weight gain, and survival data were evaluated. The mechanisms, such as COX-2 expression and activity, oxidative stress, by means of enzymes and lipoperoxidation levels, and apoptosis mediators were also investigated. A reduction in tumor growth and an increased weight gain were observed. Celecoxib provided a higher incidence of survival compared with the control group. Cellular effects are probably COX-2 independent, because neither enzyme expression nor its activity, measured by tumoral PGE(2), showed significant difference between groups. It is probable that this antitumor action is dependent on an apoptotic way, which has been evaluated by the expression of the antiapoptotic protein Bcl-xL, in addition to the cellular changes observed by electronic microscopy. Celecoxib has also a possible involvement with redox homeostasis, because its administration caused significant changes in the activity of oxidative enzymes, such as catalase and superoxide dismutase. These results confirm the antitumor effects of celecoxib in W256 cancer model, contributing to elucidating its antitumoral mechanism and corroborating scientific literature about its effect on other types of cancer.

Insulin suppresses LPS-induced iNOS and COX-2 expression and NF-kappa B activation in alveolar macrophages

The development of septic shock is a common and frequently lethal consequence of gram-negative infection. Mediators released by lung macrophages activated by bacterial products such as lipopolysaccharide (LPS) contribute to shock symptoms. We have shown that insulin downregulates LPS-induced TNF production by alveolar macrophages (AMs). In the present study, we investigated the effect of insulin on the LPS-induced production of nitric oxide (NO) and prostaglandin (PG)-E(2), on the expression of inducible nitric oxide synthase ( iNOS) and cyclooxygenase (COX)-2, and on nuclear factor kappa B (NF-kappa B) activation in AMs. Resident AMs from male Wistar rats were stimulated with LPS (100 ng/mL) for 30 minutes. Insulin (1 mU/mL) was added 10 min before LPS. Enzymes expression, NF-kappa B p65 activation and inhibitor of kappa B (I-kappa B) a phosphorylation were assessed by immunobloting; NO by Griess reaction and PGE(2) by enzyme immunoassay (EIA). LPS induced in AMs the expression of iNOS and COX-2 proteins and production of NO and PGE(2), and, in parallel, NF-kappa B p65 activation and cytoplasmic I-kappa B alpha phosphorylation. Administration of insulin before LPS suppressed the expression of iNOS and COX-2, of NO and PGE(2) production and Nuclear NF-kappa B p65 activation. Insulin also prevented cytoplasmic I-kappa Ba phosphorylation. These results show that in AMs stimulated by LPS, insulin prevents nuclear translocation of NF-kappa B, possibly by blocking I-kappa Ba degradation, and supresses the production of NO and PGE(2), two molecules that contribute to septic shock. Copyright (C) 2008 S. Karger AG, Basel.

Black-box decomposition approach for computational hemodynamics: One-dimensional models

Increasing efforts exist in integrating different levels of detail in models of the cardiovascular system. For instance, one-dimensional representations are employed to model the systemic circulation. In this context, effective and black-box-type decomposition strategies for one-dimensional networks are needed, so as to: (i) employ domain decomposition strategies for large systemic models (1D-1D coupling) and (ii) provide the conceptual basis for dimensionally-heterogeneous representations (1D-3D coupling, among various possibilities). The strategy proposed in this article works for both of these two scenarios, though the several applications shown to illustrate its performance focus on the 1D-1D coupling case. A one-dimensional network is decomposed in such a way that each coupling point connects two (and not more) of the sub-networks. At each of the M connection points two unknowns are defined: the flow rate and pressure. These 2M unknowns are determined by 2M equations, since each sub-network provides one (non-linear) equation per coupling point. It is shown how to build the 2M x 2M non-linear system with arbitrary and independent choice of boundary conditions for each of the sub-networks. The idea is then to solve this non-linear system until convergence, which guarantees strong coupling of the complete network. In other words, if the non-linear solver converges at each time step, the solution coincides with what would be obtained by monolithically modeling the whole network. The decomposition thus imposes no stability restriction on the choice of the time step size. Effective iterative strategies for the non-linear system that preserve the black-box character of the decomposition are then explored. Several variants of matrix-free Broyden`s and Newton-GMRES algorithms are assessed as numerical solvers by comparing their performance on sub-critical wave propagation problems which range from academic test cases to realistic cardiovascular applications. A specific variant of Broyden`s algorithm is identified and recommended on the basis of its computer cost and reliability. (C) 2010 Elsevier B.V. All rights reserved.

Transformed generalized linear models

The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.

Second-order negative-curvature methods for box-constrained and general constrained optimization

A Nonlinear Programming algorithm that converges to second-order stationary points is introduced in this paper. The main tool is a second-order negative-curvature method for box-constrained minimization of a certain class of functions that do not possess continuous second derivatives. This method is used to define an Augmented Lagrangian algorithm of PHR (Powell-Hestenes-Rockafellar) type. Convergence proofs under weak constraint qualifications are given. Numerical examples showing that the new method converges to second-order stationary points in situations in which first-order methods fail are exhibited.